4d

And now, for first time on television, we present to you the interview with Eric Green, taken by Patricia Stone.
- Hello Eric, and welcome to our studio.
- Hello Patricia, it's a pleasure.
- Your story made world news, but some of our audience might have missed the details, before we move on with the questions, could you describe to them what happened to you, and why that changes the world as we know it.
- I managed to extend my existence into a 4th dimension. You are about to ask me if time is the 4th dimension, and the answer is - no, it is not. Answering you before you asked the question might seem to contradict that, but it does not. The forth dimension is not entangled with any of the 3 dimensions we take fore granted, neither with time. It allows me to stand aside from the a specific point of the space-time and observe it's "surrounding" space-time. To make it more clear - imagine that the space-time is a line of boxes from -infinity to +infinity. If we take a one box of it to represent the current moment in time and space, I would be able to "rise" a bit above the line and thus observe what's inside the neighboring boxes. I cannot move back and forth between boxes, only observe them. Also I cannot view clearly the entire content of the boxes, due to looking to them at an angle. That allows for some uncertainty on the exact events to take place.
- So you are like a medium that can see what will happen into the immediate future?
- I do not "see" it in a form of a vision, but I feel what will happen next with some amount of certainty.
- Isn't that something that everyone does?
- It is. Only I do it with extreme success, that cannot be matched or explained by scientists.
- Can you tell us how you achieved the extending to 4D?
- It started as a project for a video game. The idea was to allow the player to act in a virtual 4D space. There are already such games in development, but they represent only 3 dimensions at a time, and you can just switch one predefined of the 3 presented with a predefined 4th one. In that sense, you never experience 4D - all the dimensions at once. I wanted to come up with a way to represent all the dimensions simultaneously.
At some point I asked myself how would 2D entities attempt to visualize the 3D, and I figured that it's impossible. We see through light, but you can use any electromagnetic wave. These waves, do not "exit" the 3D space, neither such waves "enter" in our 3D from the 4th dimension. (That is because it's not entangled with the 3D). Therefore there cannot be visual representation of the 4D. So I decided to try and observe 4D through another sense. Blindfolded I started attempting to imagine what will it be like to hold a 4D cube. It took a lot of time and there was a lot of frustration, but at one point I managed to construct a model of the sensation that holding a 4D cube will imply.
I kept on training with more and different 4D shapes. It took me a great deal of time and practice to achieve that without closing my eyes first - that was the hardest part. However with time I learned, and it became more and more easier. I started to sensory imagine various 4D extensions of real life objects. At some point I jumped to perceive 4D space - the 4D shape that was not filled by the 4D extensions of the real objects.
I discovered that my 4D view of the world is real through an accident. One day I was exercising my 4D sensuality by extending the whole office. I figured, there is overlapping of some objects, and traced them to try and repair what I though was an error on my behalf. However the reduced result implied that my colleague's coffee cup should be in pieces. The next instant I observed my colleague knocking his cup of the desk. Initially I dismissed the fact that I predicted the breaking of the cup by telling myself it was a coincidence and that I probably saw his hand move just before making the conclusion on subconscious level, and only then considering the 4D implication.
- It sounds amazing, how long ago did you start imagining the 4D?
- It was about 18 years ago.
- One of our viewers has a question: "Doesn't the 3D base allow multiple 4D extensions?"
- It does, but I always choose ones that are proportional to their 3D sizes. Often the 4D scenery greatly narrows possible extensions into the 4D. Considering the relative positions of the objects in the past also reduces the options. And the remaining different options constitute the creeping uncertainty.
- Another question from the audience: "How do people extend in the 4D?"
- Ah, you are on the right track with that question. It's nearly impossible to define the right extension for people. I tend to imagine their extension as a mist. I associate the feeling as touching a dense liquid, or jelly - it's soft and bends to the applied force, but returns to the initial form if the force is removed. Unlike jelly my perception does not have definite edge, however I imagine a sort of an envelop that defines all possible extensions inside of it. That envelop is relatively at the defined by the edge where the sensory feedback cannot be distinguished from zero. Note that it's something that I imagine, it's not a property of the shape. One might feel that interaction by human upon an object should increase the possible extensions of the scenery, but in practice it's quite the opposite. Often interaction with a well defined object reduces the person's 4D extension possibilities to just one. Human to human interaction can go both ways - my observations do not incline in any direction.
- So what you're saying is that me holding the microphone makes my future predetermined.
- If you are about to bump me on the head with the mic to prove that your actions aren't predetermined - please don't.
- Ha ha, that's incredible, I was just considering that...
- Yes, it is true, that my experiences and other senses influence the way I extend the scenery into 4D. If I wasn't using previously remembered 4D models it would be impossible to "observe" the 4D in real time. If fact we do the same thing when we view the 3D with our eyes. Over 90% of what we see is based on our memory. Looking at a light bulb gives us information of a bright spot. It's our memory that gives us info on what's behind the glare. It's the same with interpreting visual information based on knowledge of our environment. When you are on a train and look at a passing closely by column, what you get as visual information is a smeared bit of gray. Our knowledge of being on the train and that it's common that the same column we saw at the station, to repeat along the tracks, that allows us to interpret the visual data.
- Many of our viewers still believe that your abilities are a hoax, and cannot accept the implications that they imply, how does that make you feel?
- I understand them. I feel a bit sorry for them, because that means they cannot adapt well to the new understanding of the world. The new concept will find applications in real life and sooner or later they will have to embrace it if they want to fall behind from the rest of the world.
- Do you plan to extend to 5D any time soon?
- No, I don't. I plan to work on making the sensory mapping more precise, and I hope this will allow me to peer a bit further into the future.
- Thank you Eric for the time, and I wish you luck with your endeavor.
- Thank you, and good night.

Iliyan Bobev, Copyright 2010.

Утре започва от днес - защо смятам че протеста трябва да продължи

Проблема не е само във избора на Пеевски, проблема е в начина по който той беше избран. Проблема е че това беше допуснато да се случи. Все още не са признали че този човек е неподходящ за позицията - шикалкавят за това че не преценили реакцията. Промените гласувани в закона са ясно доказателство че поста е нагласен за определен човек - нямали са намерение да "избират", всичко е било решено. Абсурдно е законите да се пишат и гласуват за удобството на отделни хора. Доказатествата са обнародвани в Държавен вестник.

Това е моята гражданска позиция - на протеста съм, защото целия смисъл на прехода се състои в това. За разлика от времето преди 1989г. можем да го направим без да се срахуваме. Но не тряба да забавяме, че гражданската позиция не е само привилегия а е дълг. Дължим го най-малко на родителите си, които се бориха за това, а и много повече на децата си, които ще взимат пример от нас за да се справят сами с проблемите утре.

#ДАНСwithme

mysteries of the universe

I just love the closing words to this video:
http://www.youtube.com/watch?v=L45Q1_psDqk&feature=youtu.be&t=10m

Thoughts on Gold’s Theorem

Thoughts on Gold's Theorem and article "Gold’s Theorem and cognitive science"

http://psyling.psy.cmu.edu/papers/years/2004/logical/gold-johnson.pdf

* Gold's Theorem *

(short representation of the theorem as I understand it)

I. Given an environment E and a language L, the learner learns L given E if there is some time tn such that at tn and all
times afterward, the learner correctly guesses that L is the target language present in the environment. (Gold himself called this condition "identification in the limit".)

 In my opinion, that is to say that someone has learned a language after she starts to distinguish the properly formed sentences from the improper ones in respect to language L.

II. Let's deconstruct a language to a set of languages, each differing with one sentence, which is invalid in Ln but is valid in Ln+1. This set is infinite and each language is contained in all subsequent. The last one Linf, would contain all sentences from all other languages in the set.

III. Theorem states that function F that properly recognizes the language given a set of example sentences will either never converge for Linf or it will jump to Linf without properly converging on some of the previous sub-language.

 Formal definition: (GT) Any class of languages with the Gold Property is unlearnable.
 Where class of languages with the Gold Property is the infinite deconstruction set of a language.

* Interpretation *

My interpretation is that the "Golden Property" actually can only be observed in a language deconstruction set. Therefore the theorem concerns a single language and it unlearnability via expanding set of examples. Therefore I think that the whole premise in the article is flawed.

* Alternative presentation of the theorem *

Here's how I would cover the same concept:
a) language is infinite as there are infinitely many sentences that would conform with its grammar;
b) decomposing the language in sub-languages differing by a single sentence forms infinite set which complies with the "golden rule";
c) negative evidence - examples of incorrect sentences, will be points lying outside the vector representing the language;
d) Learning language is establishing a function that determines whether a point belongs to the vector;
Prove:
Let the language be a vector, and each proper sentence of it is a point on that vector; that makes each sub-language a represented as line segment. Given a set of dots on that vector, they will always be contained in more than one line segment. Successful learning the language will always rely on a "projection" of the received data points in order to encompass the vector and its infiniteness. Therefore the knowledge of a language is more than a set of proper examples and negative evidence.

* Thoughts on the Model *

I like to develop this generic model further by allowing the exceptions of the grammar rules to lay outside of the vector. Ideally each rule will define a plane in multidimensional space and the intersection of the planes will define the vector for the language. Some tensor will encompass the the vector and all the exception points. Then the volume of that tensor may be used to define the difficulty of learning that language. Or we can set the volume of the tensor encompassing 95% of all proper sentences, because one exception laying far from the vector may cause more volume than many that are closer. Such model also accounts for the fact that projection (of samples to vector), alone, is also insufficient to provide learning of the language. A lot of samples will be required on top of the projection in order to account for all exceptions.
How we form the space - if we use as many dimensions as there are grammar rules in the language, the end result will be a single point, as each rule eliminates one dimension out. To bring this to one dimensional result we add a dimension enumerating the set of all proper sentences. Bringing this in to view with the exceptions laying outside of the vector, we are to say that there are alternative vectors originating from the same point obeying the all rules, but defining different set, which is wrong.
So we need to start with all possible sentences, regardless of language. Then we start to chop down dimensions for each grammar rule we add. But there is no guarantee the end result will be a line, it might as well be a plane. That doesn't change the concept of having exceptions of the rules lie outside of the rule restricted region, but provides insight to why the language acquisition is difficult - the more dimensions there are in the final region, the more difficult it will be to obtain a function that determines if a point belongs to the proper grammar.
There is another aspect of language that may be represented in the model - the ***. There are many sentences that follow proper grammar, but we do not see in the day to day language use. These could be many, but let's take one example - "Noun is very very very very very ... very adjective". We can see sentences with 2-3 times "very" in them, but one with more than 5 starts to seem odd. And technically we can have infinitely many times the word "very" without breaking the grammar. This indicates that there are whole segments in the multidimensional language shape that are not used. Introducing some additional (soft) rules will definitely reduce the language volume and its dimensionality. These additional rules should be soft, since they can still find use in some fringe situations.

* End thoughts *

- Overall I am convinced that the both rationalist and empiricist approach are needed to explain language acquisition.
- Learning a language is not a discrete event.
- Natural languages are not strictly defined.
- Even grammatical rules are "soft" and breaking them does not necessarily prevent communication.

Iliyan Bobev 2013 (c) all rights reserved.

Chomsky vs Norvig

I respect Peter Norvig, and there is no denial that he has made many contributions to science, but in this argument I tend to side with Chomsky, and here's why:

Articles sources:

Chomsky: http://www.theatlantic.com/technology/archive/2012/11/noam-chomsky-on-where-artificial-intelligence-went-wrong/261637/?single_page=true

Norvig: http://norvig.com/chomsky.html

Short Q-A-Comment exert:

Norvig: I take Chomsky's points to be the following:

Chomsky: Statistical language models have had engineering success, but that is irrelevant to science.
Norvig: I agree that engineering success is not the goal or the measure of science. But I observe that science and engineering develop together, and that engineering success shows that something is working right, and so is evidence (but not proof) of a scientifically successful model.
Bobev: The engineering success in the current case can only be evidence of "something working right" with the statistical model - and it's long proven that statistics is scientifically successful model.

Chomsky: Accurately modeling linguistic facts is just butterfly collecting (I'd use "cataloging butterfly in attempt to determine how they fly"); what matters in science (and specifically linguistics) is the underlying principles.
Norvig: Science is a combination of gathering facts and making theories; neither can progress on its own. I think Chomsky is wrong to push the needle so far towards theory over facts; in the history of science, the laborious accumulation of facts is the dominant mode, not a novelty. The science of understanding language is no different than other sciences in this respect.

Bobev: I agree that science is about gathering facts, but in the current case the facts being gathered do not find application in science, but in engineering. What's the scientific value can be derived by the fact that the probability of "am" following "I" is say 50% ? Any other facts, are relative to the automation and resolving difficulties of obtaining and sorting and storing these probabilities. In the same time, there is very little done for obtaining, sorting and analyzing languages.

Chomsky: Statistical models are incomprehensible; they provide no insight.
Norvig: I agree that it can be difficult to make sense of a model containing billions of parameters. Certainly a human can't understand such a model by inspecting the values of each parameter individually. But one can gain insight by examining the properties of the model—where it succeeds and fails, how well it learns as a function of data, etc.

Bobev: As Chomsky says, it's not that statistical model cannot provide any insights, but it cannot provide insights to the question we are interested in: How does the brain use language on physiological level.

Chomsky: Statistical models may provide an accurate simulation of some phenomena, but the simulation is done completely the wrong way; people don't decide what the third word of a sentence should be by consulting a probability table keyed on the previous two words, rather they map from an internal semantic form to a syntactic tree-structure, which is then linearized into words. This is done without any probability or statistics.
Norvig: I agree that a Markov model of word probabilities cannot model all of language. It is equally true that a concise tree-structure model without probabilities cannot model all of language. What is needed is a probabilistic model that covers words, trees, semantics, context, discourse, etc. Chomsky dismisses all probabilistic models because of shortcomings of particular 50-year old models. I understand how Chomsky arrives at the conclusion that probabilistic models are unnecessary, from his study of the generation of language. But the vast majority of people who study interpretation tasks, such as speech recognition, quickly see that interpretation is an inherently probabilistic problem: given a stream of noisy input to my ears, what did the speaker most likely mean? Einstein said to make everything as simple as possible, but no simpler. Many phenomena in science are stochastic, and the simplest model of them is a probabilistic model; I believe language is such a phenomenon and therefore that probabilistic models are our best tool for representing facts about language, for algorithmically processing language, and for understanding how humans process language.

Bobev: I totally agree that the two approaches should be combined at some point. What I'm unhappy about is that the current focus of the entire field is on probabilistic model. Every new paper is based solely on statistics.

Chomsky: Statistical models have been proven incapable of learning language; therefore language must be innate, so why are these statistical modelers wasting their time on the wrong enterprise?
Norvig: In 1967, Gold's Theorem showed some theoretical limitations of logical deduction on formal mathematical languages. But this result has nothing to do with the task faced by learners of natural language. In any event, by 1969 we knew that probabilistic inference (over probabilistic context-free grammars) is not subject to those limitations (Horning showed that learning of PCFGs is possible). I agree with Chomsky that it is undeniable that humans have some innate capability to learn natural language, but we don't know enough about that capability to rule out probabilistic language representations, nor statistical learning. I think it is much more likely that human language learning involves something like probabilistic and statistical inference, but we just don't know yet.

Bobev:  I agree that we cannot rule out involvement of probabilistic element in some aspects of language use, but I think it's pretty obvious that the language cannot be based only on probabilistic representation. I cannot cite who proved what when, but I know that if I can "invent" new words, and other people still understand me, I have bridged any statistical representation of the language, but I'm still adhering to the language model used by the mind. What you work with is a statinguage - how can statistical model handle that?

In-line comments on some points made by Norvig

Norvig:  If you have a vocabulary of 100,000 words and a second-order Markov model in which the probability of a word depends on the previous two words, then you need a quadrillion (10^15) probability values to specify the model. The only feasible way to learn these 10^15 values is to gather statistics from data.
Bobev: @4bytes per Float value, that makes 3.5 petabytes, and the most generous estimations of human brain capacity for non-chemical storage is 2.5 petabytes. But even if we allow for chemical storage, or if we assume that brain stores data at 1byte per Float value, the language we use is 300 000 words, which will require much more than the 10^15. And if we go to third-order Markov model? And what of learning 2nd language? And what of all other knowledge or memories? For me it's obvious, that we do not store such info in our brains. So if our brains use language more efficiently and correctly at the same time, there must be a different representation of language in the mind.

Norvig: Clearly, it is inaccurate to say that statistical models (and probabilistic models) have achieved limited success; rather they have achieved a dominant (although not exclusive) position.
Bobev: statistical models (and probabilistic models) have achieved no success in explaining how language is represented or used in our mind or on a physiological level. Statistical models are dominant at specific language based contests/tasks, because they are cheats - they strive to replicate only the outcome, but not the process. And all the "progress" is due to computation power - after all the Bayesian networks have not changed since 1980s. I consider useful the hybrid models, if they provide some understanding of how to incorporate statistical and rules based processing.

Norvig: Another measure of success is the degree to which an idea captures a community of researchers. As Steve Abney wrote in 1996, "In the space of the last ten years, statistical methods have gone from being virtually unknown in computational linguistics to being a fundamental given. ... anyone who cannot at least use the terminology persuasively risks being mistaken for kitchen help at the ACL [Association for Computational Linguistics] banquet."
Bobev: That is exactly why I'm so upset. Many researchers have been pushed towards statistical methods by conformity. The rapid success of the engineering aspect of the field created a lot of hype, which has shifted a lot of interest, support and funding from the goals understanding how it works, instead of simulating results.

Norvig: A dictionary definition of science is "the systematic study of the structure and behavior of the physical and natural world through observation and experiment," which stresses accurate modeling over insight,...
Bobev: Wait, what? 1) I don't find a mention of "modeling" in that definition, let alone a stressed one. 2) If you want to read "study of the structure and behavior" as "modeling", it should be more in the notion of "discover underlining model" rather than "create a model that simulates". It's important to clarify what you will study exactly, because it's one thing to study the human use of the language, and another to study machine use of language.

Norvig: It certainly seems that this article is much more focused on "accurately modeling the world" than on "providing insight."
Bobev: Again, where do you see modeling? Science aims at understanding the what governs the observed phenomenon - if the paper addresses the efficiency of some electrodes, it's doing so in order to explain why. Scientists do experiments to confirm specific idea - insight if you will. The subject involved with striving to create a system that yields specific results is engineering - the outcomes of that process are called "prototypes", not "experiments". 

Norvig: and for the 2010 Nobel Prizes in science:
Physics: for groundbreaking experiments regarding the two-dimensional material graphene
Chemistry: for palladium-catalyzed cross couplings in organic synthesis
Physiology or Medicine: for the development of in vitro fertilization
My conclusion is that 100% of these articles and awards are more about "accurately modeling the world" than they are about "providing insight," although they all have some theoretical insight component as well. I recognize that judging one way or the other is a difficult ill-defined task, and that you shouldn't accept my judgements, because I have an inherent bias.
Bobev: Well, you got it wrong. Unless they have the theoretical insight "component" (probably more of a core, really), no one would consider them science. There is some rule of thumb in science, that says that experiments should be chosen so that they can clearly prove or disprove a hypothesis that you have already formed. There are of course accidental discoveries, and sometimes throwing a random experiment with no clear goal or idea, might set you on the right track, but even with this approach you have to fit the results in theory insight.

Norvig:  I repeated the experiment, using a much cruder model with Laplacian smoothing and no categories, trained over the Google Book corpus from 1800 to 1954, and found that (a) is about 10,000 times more probable. If we had a probabilistic model over trees as well as word sequences, we could perhaps do an even better job of computing degree of grammaticality.
Furthermore, the statistical models are capable of delivering the judgment that both sentences are extremely improbable, when compared to, say, "Effective green products sell well." Chomsky's theory, being categorical, cannot make this distinction; all it can distinguish is grammatical/ungrammatical.
Bobev: OK, let's place the probability results for these three sentences in scale - plot them on interval (0,1). You haven't provided the exact values, but I have some idea of what numbers are yielded from these statistics. The first two sentences are so close to 0, that you feel it wont be in favor of your argument to show all the zeroes between the decimal point and the meaningful numbers. In that respect the first two sentences might differ by 10,000 times, and still be really close at each other, being in the zone of 10^-15 as a value. Now these two sentences might have got the right probability order just as a fluke - I seriously doubt that the same results will be yielded with the same sentences, but with the color replaced. Go through all the colors and let me know if the results aren't wrong, at least at 50% of the time. 
And why would we care that there is some other sentences that is extremely more probable? What has it to do with determining whether a given sentence is grammatical? Because that's what we need. If we as humans can determine if a sentence is grammatical or not with certainty, the desired model should be able to do the same. Only then, we can argue that such model may be physiologically implemented in the human brain. 

Norvig: "All grammars leak."
Bobev: Agreed. We need to incorporate statistics in modeling human use of language, but it's more than just probabilities.

Norvig: Since people have to continually understand the uncertain. ambiguous, noisy speech of others, it seems they must be using something like probabilistic reasoning. Chomsky for some reason wants to avoid this, and therefore he must declare the actual facts of language use out of bounds and declare that true linguistics only exists in the mathematical realm.
Bobev: I don't think Chomsky wants to avoid the use of probabilistic methodology, but rather that he's "concerned with discovering a mental reality underlying actual behavior" in humans. He believes that such is the goal of linguistics, and you believe it's the creation of "statistical (or probabilistic) models, which while accurately modeling reality, do not make claims to correspond to the generative process used by nature". 
Conclusion: So the whole thing is comparing apples and oranges -- you simply strive for different things.

I personally do not care what's the goal of linguistics as a science, but I tend to side with Chomsky in the view that efforts for making models which "make no claim to correspond to the generative process used by nature" are of no use (or are detrimental) for discovering what underlines actual behavior in language use.

IMHO the only way to advance both aspects (accurate modeling and discovering the process used by nature) is to go hybrid.

I think the movie "In the Mood for Love" is great

Recently I watched a VSause video: http://youtu.be/i8tHWPRPF9M ,
which led me to http://www.youtube.com/watch?v=JnQmJaqUJ0Y&feature=share&list=SP77A0EB0EAF0FEFEB

As the authors of the show suggest, it's best to watch the movie first and then view the discussion of it - that's how I did it. Same is valid for the comments below - I'll try to avoid spoilers, but it's best to make your own impressions first.

So I watched the movie In the mood for love by Kar Wai Wong and I really liked it, and here is why:
I love the visuals and style - they are vivid, consistent and inspiring. The scene of the corridor with red drapes is unforgettable. Pacing came a bit slow for me, but it was worth it, and probably helps the emotional build up. The technique of having the protagonists practice what they want to do, but never did, was very effective for me. Music was also well used to portray the mood.
In terms of story, I think that society has changed a lot since the 60s and today people in the same situation would definitely choose to their own happiness instead of adhering to the society expectations. Non the less, the emotions portrait would still be vibrant and tangible today, as they were years ago. That makes the story transcend the choice of time and place, and that's what makes it great.
It's not a movie that will stun you, but it's a movie that will make you feel, and think, and that is something. It stands out, compared to the tons of meaningless films pouring out of Hollywood these days.
I will definitely explore more of the works of  Kar Wai Wong.

I think that the movie Dark Knight Rises is weak

Few days ago I strongly expressed my opinion of the Dark Knight Rises, which is that the movie is weak. Here are some of the arguments I presented in the subsequent argument.
Although the movie at the moment has score of 8.8 in IMDB at the moment, it failed to meet my expectations. I don't think that meeting the expectations of 0.5 million people, makes it good, and only means that many people have low expectations.
I do admit that my opinion is subjective, because I really liked the previous film, and that set the bar high for this installment. If I haven't previously watched The Dark Knight, I would have probably have given the current film higher score. I might have presented my opinion quite expressively, and I beg that to be excused on account of my strong emotional affection derived on part of subjective factors. However although the subjective might have affected my reaction, there are a lot of objective aspects of the film that cannot be regarded as other than weak.
Although the film was compared with other movies based on comics, I do not think that is correct, as the common source of ideas does not correspond to equality in genres. I find Ironman and Avengers to gravitate towards comedy, while The Dark Knight trilogy is more of a drama. Therefore I expect different depth and effort form these different movies.
I also need to mention that there are still may elements in the Dark Knight Rises that I like, but they cannot outweigh the fails, and the overall evaluation remains negative. Similarly I have very positive opinion on the The Dark Knight, but it's far from perfect. I find many issues, but they are not in the core elements and can be ignored.
SPOILERS SPOILERS SPOILERS SPOILERS SPOILERS 
to avoid spoilers stop reading here
Lets dive in with some examples and comparisons:
One of the things that tilted the scales in the negative direction, was the interruption of the story tempo. Everything was flowing orderly, until the placed our hero in the well prison, and then the time jumped ahead for moths, and suddenly our hero from beaten and sick, became healthy and strong. Besides breaking the story line, that also is a cheat. The hero is a hero, because he overcomes his weaknesses through suffering and pain, thanks to his will. This is totally hidden in this case, as if the passing of time is the only prerequisite for the hero to be reborn with the qualities needed to pass previously impassible obstacles. Compare that with The Count of Monte Cristo - which is more realistic and believable. If man is imprisoned, he gets crushed.The man is deprived of freedom and future has to find new hope in order to prevail. In the Count, the protagonist suffers, and from the suffering he reforms. In The Shawshank Redemption the main character suffers the usual unpleasantness, before he realizes there is something deep inside your body, that people can't touch and get to....'HOPE'. In Batman, the whole thing is presented so short, it fails to represent the suffering. The idea is clearly there, but the execution destroys it. Here should be the essence of the film, and what I got is that in one scene he gets up of the floor, on the second 5 push-ups, and on the third he's climbing the wall. I get the feel that the author wants to show how the protagonist finds new hope and new purpose, but I don't see that he lost it in first. They especially elaborate that the prison is designed to crush hope by first giving it in the form of the patch of sky, and then taking it away by the repetitive failure of the escape attempts. Well it didn't work and I didn't see the character feeling imprisoned i.e. crushed. This results in no clear trigger of the internal change. Was it the life in well? The few words of a cellmate in a foreign language? Was it the images on the TV screen in the cell? Or some graffiti on the prison wall they never showed? There had to be some change happening, because Alfred was telling him the same thing from the start "you need purpose in life", yet then it had no effect. The entire part of felt as if getting out was the most natural thing, that they let him go out through the front door. I think this portion of the story had to be presented in much more detail, as it's the resolution to the hero's dilemma, but instead it's fragmented and pretty much ignored.
I find most of the characters in the movie bleak and incomplete. In fact the two characters that I think are built fine, are Alfred and Blake. The worst character is the Peter Foley (Deputy Police Commissioner). He is presented so weak and incompetent while there is no explanation why is there such a man on a position of significance that demands the opposite qualities. How did he ended  in the police force,  instead of fast food. But lets assume that author didn't bother with secondary character, and compare the main villains in the last two films - The Joker and Miranda. From the Jokers actions the viewer can determine that his motives are desire for chaos and anarchy, he wants to prove to the world that even in the most exemplar and honest man, can be corrupted, that everyone that stands for the 'good' carries the capacity for 'bad'. To the world, the Joker himself, presented his goals as 'exposing the corruption', which adds another layer to the character - how he wants to present himself, and potentially how he manages to win followers to his side. It is made clear that his view of the world is result of traumatic childhood, which makes the character very believable. I can't find any strong motivators that would explain the actions by Miranda, so I have to speculate. Does she want to avenge her father, or does she want to complete what he started? What in her character explains her strong determination? Is it love or grief that makes her ready to kill millions and sacrifice herself in the process? Usually, when someone is willing to sacrifice his life, it's for a idea or a cause that will live on past them. It's clear for the Joker - if Batman kill him, that will be a prove that Batman is both the judge and the executor, and that is not justice. Miranda never tells the world that this is her vengeance, so what will she prove if her plan got carried out? And why is she on this path in first place? Her father got killed because he was planning  to kill many people (and I don't remember the first movie that well, but might have been an accidental death). I recon a normal people don't rush to carry out the legacy project for mass murder, even if that project belonged to their father. So for her following that goal will require for her father to have won her trust, first as a person. Then to convince her in his values, and win her to the cause. I find it much more realistic when kids rebel against their parents, instead of blindly following them.
The main idea of the two movies also differs and I'll try to compare them next.
In the Dark Knight the main idea is less explored and much more interesting. The dilemma is whether to accept the guilt of another if that will keep an idea alive. If one is ready to sacrifice his life for idea, he should be ready to sacrifice his honor for the idea. But there is a twist, death might be preferable to life filled with the hate and resentment of the ones you have sacrificed for.
What's the main idea of the Dark Knight Rises, what's the protagonist's dilemma? As I mentioned previously, I think that the main character struggles with finding new hope and purpose in life. I believe that something happened while the character was in the well, something that got him what he couldn't find for 7 years. And since I cant clearly state what that something is, the author didn't do a good job on carrying out the main idea of the story.

I may continue this, if the argument I'm in, carries on